Product Question Answering in E-Commerce: A Survey

February 16, 2023 ยท The Cartographer ยท ๐Ÿ› Annual Meeting of the Association for Computational Linguistics

๐Ÿ“š THE CARTOGRAPHER: The Cartographer
Survey/review paper โ€” maps the landscape rather than implementing a method.

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"Title-pattern auto-detect: Product Question Answering in E-Commerce: A Survey"

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Authors Yang Deng, Wenxuan Zhang, Qian Yu, Wai Lam arXiv ID 2302.08092 Category cs.CL: Computation & Language Cross-listed cs.IR Citations 19 Venue Annual Meeting of the Association for Computational Linguistics Last Checked 23 hours ago
Abstract
Product question answering (PQA), aiming to automatically provide instant responses to customer's questions in E-Commerce platforms, has drawn increasing attention in recent years. Compared with typical QA problems, PQA exhibits unique challenges such as the subjectivity and reliability of user-generated contents in E-commerce platforms. Therefore, various problem settings and novel methods have been proposed to capture these special characteristics. In this paper, we aim to systematically review existing research efforts on PQA. Specifically, we categorize PQA studies into four problem settings in terms of the form of provided answers. We analyze the pros and cons, as well as present existing datasets and evaluation protocols for each setting. We further summarize the most significant challenges that characterize PQA from general QA applications and discuss their corresponding solutions. Finally, we conclude this paper by providing the prospect on several future directions.
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